Optical coherence tomography detection method for thermally grown oxides in aircraft engines

Abstract

The present invention discloses an optical coherence tomography detection method for thermally grown oxides in aircraft engines, relating to the field of optical detection. The method comprises: collecting interference signals between a reference light field and a scattered light field of a sample; performing adaptive polarization state compensation on the interference signals based on a dynamic polarization matching factor to obtain a compensated interference signal; performing anisotropic filtering on the compensated interference signals to separate the columnar crystal structure characteristics of the oxide layer and obtain a filtered signal; performing time-frequency joint analysis on the filtered signals, optimizing the time-frequency transform kernel parameters using an adaptive window width adjustment factor, and extracting the oxide layer thickness and frequency band energy distribution; fusing the columnar crystal structure characteristics with the frequency band energy distribution to construct a cross-scale thermodynamic inversion model and output a prediction result for the remaining life of the engine's thermally grown oxide layer. By introducing polarization compensation, frequency domain analysis optimization, and a multi-field coupled inversion model, the imaging clarity, thickness extraction accuracy, and remaining life prediction capability of the thermally grown oxide layer are significantly improved.

Description

Technical Field

[0001] The present invention relates to the field of optical detection, in particular to an optical coherence tomography detection method for thermally grown oxides of aircraft engines. Background Art

[0002] During service, aircraft engines are exposed to harsh operating conditions such as high temperature, high pressure, high-velocity airflow, and an oxidizing atmosphere, often leading to thermal growth and oxidation on the surfaces of their hot-end components. The continued growth of the oxide layer degrades the material's microstructure, reducing its thermal barrier properties and mechanical strength, and is a key factor in reducing service life and even component failure. Therefore, accurately detecting the geometric characteristics and microstructural evolution of thermally grown oxides is crucial for ensuring engine service safety and conducting life prediction and assessment.

[0003] Optical coherence tomography, a high-spatial-resolution, non-contact three-dimensional imaging technology, has demonstrated significant potential in recent years for material microstructure detection. However, standard OCT imaging often suffers from signal degradation due to uneven light scattering and polarization perturbations in complex, multi-scattering media, such as thermally grown oxide layers. This in turn limits its ability to resolve microstructural features and accurately detect thickness variations. Furthermore, existing OCT detection methods have yet to incorporate crystal structure information for physical modeling and lifespan prediction, making it difficult to accurately assess the evolutionary behavior of thermally grown oxide layers in the complex service environments of aircraft engines.

[0004] Therefore, there is an urgent need for an OCT detection method for thermally grown oxides that integrates polarization compensation, adaptive filtering, frequency domain analysis, and cross-scale modeling to improve the ability to identify the microstructure of thermally grown oxide layers, enhance the modeling accuracy of their thickness and thermodynamic evolution laws, and achieve an organic fusion of non-destructive, high-resolution, and remaining life prediction. Summary of the Invention

[0005] Based on the above-mentioned shortcomings of the prior art, the purpose of the present invention is to provide an optical coherence tomography detection method for thermally grown oxides in aircraft engines to solve the above-mentioned technical problems.

[0006] To achieve the above-mentioned object, the present invention provides the following technical solution: an optical coherence tomography detection method for thermally grown oxides in aircraft engines, comprising:

[0007] S1: Collect the interference signal between the reference light field and the sample scattered light field, perform adaptive polarization state compensation on the interference signal based on the dynamic polarization matching factor, and obtain the compensated interference signal;

[0008] S2: Anisotropic filtering is performed on the compensated interference signal. The signal discontinuity at the columnar grain boundary is retained by constraining the grain boundary discontinuity index, and the columnar crystal structure characteristics of the oxide layer are separated to obtain the filtered signal.

[0009] S3: Perform time-frequency joint analysis on the filtered signal, optimize the time-frequency transform kernel parameters using the adaptive window width adjustment factor, and extract the oxide layer thickness and frequency band energy distribution;

[0010] S4: Integrate the columnar crystal structure characteristics and frequency band energy distribution to construct a cross-scale thermodynamic inversion model and output the remaining life prediction results of the engine thermal growth oxide layer.

[0011] The present invention is further configured as follows: the interference signal between the reference light field and the sample scattered light field is collected, the interference signal is analyzed, the phase information of the analyzed signal is extracted, the dynamic polarization matching factor is calculated, a sparse regularized optimization problem is constructed, the polarization compensation matrix is dynamically adjusted, and the polarization state of the interference signal is corrected using the updated polarization compensation matrix to obtain the compensated interference signal.

[0012] The present invention is further configured such that the dynamic polarization matching factor is dynamically updated by the sparsity constraint of the phase gradient tensor product and the polarization compensation matrix, and its expression is: ,in, is the dynamic polarization matching factor, is the spatial phase gradient, is the phase distortion field, is the Frobenius norm, is the Jones matrix traces, is the Jones matrix The conjugate transposed matrix of is the adjustment parameter.

[0013] The present invention is further configured as follows: a depth-resolved diffusion model is constructed based on the anisotropic dielectric tensor of the columnar crystal structure of the oxide layer, the sudden change intensity of the dielectric constant is quantified by the grain boundary discontinuity index, and the signal discontinuity is retained during the weighted constraint filtering process, an iterative algorithm is used to solve the joint optimization problem of the anisotropic diffusion equation and the grain boundary constraint, the columnar crystal structure characteristics of the oxide layer are separated, and the filtered signal is obtained.

[0014] The present invention is further configured such that the grain boundary discontinuity index is calculated by a normalized ratio of a dielectric constant mutation to a grain size, and its expression is: ,in, is the grain boundary discontinuity index, and is the dielectric constant on both sides of the grain boundary, is the depth position, is the average grain diameter, is the system axial resolution, Represents the dielectric constant component The second moment of is defined as: ,in, is the total number of sampling points in the depth direction of the oxide layer, is the depth position.

[0015] The present invention is further configured such that the performing time-frequency joint analysis on the filtered signal comprises:

[0016] Adaptive window width adjustment factor is used to optimize the time-frequency transform kernel parameters;

[0017] The optimal time-frequency distribution is generated by maximizing the weighted fitness function of the frequency band energy and signal-to-noise ratio through a genetic algorithm;

[0018] The band energy is nonlinearly compressed based on the hyperbolic tangent function, and the weighted summation of the coefficients calibrated by the oxidation kinetics Arrhenius equation is combined. The Sigmoid function is used to map the energy to the physical thickness range to extract the oxide layer thickness and band energy distribution.

[0019] The present invention is further configured such that the adaptive window width adjustment factor is calculated by the elastic coefficient of the frequency band energy to the window scale parameter and the frequency shift cutoff matching degree, and its expression is: ,in, is the adaptive window width adjustment factor, is the total number of frequency bands, For the Band energy, is the window scale parameter, Calculate the frequency band energy elastic coefficient, Calculate the frequency shift cutoff matching degree, For the Band shift parameters, is the cutoff frequency, .

[0020] The present invention is further configured such that the cross-scale thermodynamic inversion model construction includes:

[0021] Combining the columnar crystal structure characteristics with the band energy distribution, a multi-field coupled constitutive equation is established, in which the oxidation activation energy is corrected by the grain boundary discontinuity index, and the stress index is modulated nonlinearly by the band energy.

[0022] The parameters of the oxide growth rate equation are solved based on the Bayesian Markov Chain Monte Carlo inversion method, and the uncertainty of the remaining lifetime prediction is quantified in combination with Monte Carlo simulation.

[0023] The inversion parameters are dynamically fed back to the preprocessing step to form a closed-loop optimization of detection-modeling-prediction.

[0024] The present invention is further configured such that the cross-scale thermodynamic inversion model corrects the oxidation activation energy by using a grain boundary discontinuity index, which is expressed as follows: ,in, is the maximum grain boundary discontinuity index, is the dynamic polarization matching factor, is the corrected value of oxidation activation energy, is the baseline oxidation activation energy, is the Boltzmann constant, is the absolute temperature, is the adjustment coefficient.

[0025] The present invention is further configured such that the remaining life prediction result is output by jointly solving the oxide layer growth rate equation and the Paris fatigue model, and the expression thereof is: ,in, is the remaining lifetime of the oxide layer, is the current oxide layer thickness, is the critical failure thickness, is the effective stress, is the pre-exponential factor, which represents the frequency factor of the oxidation reaction. is the ideal gas constant, is the stress index, is the oxygen partial pressure contribution coefficient, is the partial pressure of oxygen, is the oxygen partial pressure index, is the expression for the oxide layer growth rate.

[0026] The present invention provides an optical coherence tomography detection method for thermally grown oxides in aircraft engines. The method collects interference signals between a reference light field and a scattered light field of a sample, adaptively compensates the interference signals for polarization states based on a dynamic polarization matching factor, and obtains a compensated interference signal. The compensated interference signal is anisotropically filtered, and the signal discontinuity at the columnar crystal boundaries is retained by constraining the grain boundary discontinuity index, thereby separating the columnar crystal structure characteristics of the oxide layer and obtaining a filtered signal. The filtered signal is subjected to a joint time-frequency analysis, and the time-frequency transformation kernel parameters are optimized using an adaptive window width adjustment factor to extract the oxide layer thickness and frequency band energy distribution. The columnar crystal structure characteristics and frequency band energy distribution are integrated to construct a cross-scale thermodynamic inversion model, and the remaining life prediction result of the oxide layer of thermally grown oxides in the engine is output. The beneficial effects produced include:

[0027] Improved imaging quality and structure recognition capabilities: By introducing a dynamic polarization matching factor and building a sparse regularization optimization model, adaptive polarization state compensation of the interference signal is achieved. This significantly improves OCT imaging clarity and interference signal-to-noise ratio in complex multi-scattering environments, and enhances the distinguishability of columnar crystal structures in thermally grown oxide layers.

[0028] Enhance the physical relevance of frequency domain analysis and thickness extraction: An adaptive window width adjustment mechanism and genetic optimization strategy are proposed to achieve dynamic optimization of the time-frequency transform kernel function. The frequency band energy is converted into physical thickness through nonlinear mapping and oxidation kinetic modeling, improving the accuracy of thickness detection and the physical interpretation capability.

[0029] Achieve cross-scale thermodynamic behavior modeling and life prediction: Integrate crystal structure and frequency domain energy information to construct a multi-field coupled inversion model that considers the effects of grain boundary discontinuities and stress nonlinearity, and quantify the uncertainty of modeling parameters based on the Bayesian Markov Chain Monte Carlo method to achieve high-precision prediction of the remaining life of the oxide layer.

[0030] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without inventive efforts. In the drawings:

[0032] Figure 1 The flowchart of the optical coherence tomography detection method of thermally grown oxides in an aircraft engine is shown as an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0033] The following describes the embodiments of the present invention with reference to the accompanying drawings and preferred embodiments. Those skilled in the art will readily appreciate the other advantages and benefits of the present invention from the disclosure herein. The present invention may also be implemented or applied through various other specific embodiments, and the various details in this specification may be modified or altered based on different viewpoints and applications without departing from the spirit of the present invention. It should be understood that the preferred embodiments are intended only to illustrate the present invention and are not intended to limit the scope of protection of the present invention.

[0034] It should be noted that the illustrations provided in the following embodiments are merely schematic illustrations of the basic concept of the present invention. Therefore, the illustrations only show components related to the present invention and are not drawn according to the number, shape, and size of components in actual implementation. In actual implementation, the type, quantity, and proportion of each component may be changed arbitrarily, and the component layout may also be more complex.

[0035] In the following description, numerous details are discussed to provide a more thorough explanation of the embodiments of the present invention. However, it will be apparent to those skilled in the art that the embodiments of the present invention may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring the embodiments of the present invention. Example 1

[0036] Optical coherence tomography detection method for thermally grown oxides in aircraft engines, such as Figure 1 Shown, including:

[0037] S1: Collect the interference signal between the reference light field and the sample scattered light field, perform adaptive polarization state compensation on the interference signal based on the dynamic polarization matching factor, and obtain the compensated interference signal;

[0038] S2: Anisotropic filtering is performed on the compensated interference signal. The signal discontinuity at the columnar grain boundary is retained by constraining the grain boundary discontinuity index, and the columnar crystal structure characteristics of the oxide layer are separated to obtain the filtered signal.

[0039] S3: Perform time-frequency joint analysis on the filtered signal, optimize the time-frequency transform kernel parameters using the adaptive window width adjustment factor, and extract the oxide layer thickness and frequency band energy distribution;

[0040] S4: Integrate the columnar crystal structure characteristics and frequency band energy distribution to construct a cross-scale thermodynamic inversion model and output the remaining life prediction results of the engine thermal growth oxide layer.

[0041] The present invention is further configured to collect the interference signal between the reference light field and the sample scattered light field, analyze the interference signal, extract the phase information of the analyzed signal, calculate the dynamic polarization matching factor, construct a sparse regularization optimization problem, dynamically adjust the polarization compensation matrix, and use the updated polarization compensation matrix to correct the polarization state of the interference signal to obtain the compensated interference signal. Specifically, the step of obtaining the compensated interference signal includes:

[0042] Model the interference signal: ,in, is the interference signal, is the complex amplitude of the reference light field, is the complex amplitude of the scattered light field of the sample, , are the independent intensities of the reference light and the sample light, Take the real part of the complex number, is the complex conjugate of the reference light field, is the spatial position, is the time variable;

[0043] right Along the time axis Perform Hilbert transform , extract the orthogonal components: ,in, To analyze the signal, is the imaginary part after Hilbert transform, generating a component orthogonal to the original signal, is the signal envelope, which represents the intensity distribution of the interference signal. Its formula is: , is the phase field, which contains the sample depth and dynamic change information. Its formula is: , is an imaginary unit;

[0044] Calculating the Dynamic Polarization Matching Factor , construct a sparse regularized optimization problem and dynamically adjust the polarization compensation matrix: ,in, is the regularization weight, is the Jones matrix, is the phase distortion field, For an ideal light field, is the phase field after compensation, is the square of the gradient of the phase field after compensation;

[0045] Iteratively solve the sparse regularized optimization problem, when When , the alternating direction multiplier method is used to update : ,in, is the updated Jones matrix. When the iteration reaches or the maximum number of iterations is reached , the iteration is terminated;

[0046] After the update The polarization state of the interference signal is corrected: ,in, is the interference signal after compensation;

[0047] Through dynamic polarization matching and sparsity optimization, the core challenge of interference signal distortion in the high-temperature, high-turbulence environment of aircraft engines is resolved. By integrating fluid dynamics models into real-time compensation logic and combining them with the sparsity constraints of the Jones matrix, a balance is achieved between anti-interference performance, accuracy, and efficiency, providing a highly reliable solution for oxide layer detection.

[0048] The present invention is further configured such that the dynamic polarization matching factor is dynamically updated by the sparsity constraint of the phase gradient tensor product and the polarization compensation matrix, and its expression is: ,in, is the dynamic polarization matching factor, is the spatial phase gradient, is the phase distortion field, is the Frobenius norm, is the Jones matrix traces, is the Jones matrix The conjugate transposed matrix of To adjust the parameters, specifically, the spatial phase gradient By phase field The calculation formula is: ,in, , is the orthogonal coordinate axis in two-dimensional space, corresponding to the horizontal scanning direction of detection, is the transpose operator, the phase distortion field Caused by turbulence It is obtained by mixing the noise term into Constructing phase distortion field The tensor product with the spatial phase gradient, Quantized phase distortion field With spatial phase gradient The coupling strength reflects the degree of polarization mismatch. Constraint compensation matrix Sparsity to avoid overfitting;

[0049] By coupling phase gradients and distortion fields through tensor products, combined with the sparse energy constraints of the Jones matrix, a high-precision computational framework for the dynamic polarization matching factor is constructed. By integrating fluid dynamics disturbances with structural features, breakthroughs in both anti-interference capability and detection accuracy are achieved, providing key technical support for the health management of oxide layers in hot-end components of aircraft engines.

[0050] The present invention is further configured to construct a depth-resolved diffusion model based on the anisotropic dielectric tensor of the columnar crystal structure of the oxide layer, quantify the sudden change strength of the dielectric constant by the grain boundary discontinuity index and retain the signal discontinuity during the weighted constraint filtering process, and use an iterative algorithm to solve the joint optimization problem of the anisotropic diffusion equation and the grain boundary constraint to separate the columnar crystal structure characteristics of the oxide layer and obtain the filtered signal. Specifically, based on the anisotropic characteristics of the columnar crystal of the oxide layer, the principal axis component of the dielectric tensor is defined: , ,in, , , is the dielectric constant in different directions, is the substrate dielectric constant, , is the material constant, is the porosity distribution, for depth;

[0051] The porosity distribution is inverted using the interference signal envelope attenuation characteristics: ,in, is the initial amplitude, is the envelope signal, is the absorption coefficient, It represents the exponential attenuation of the signal due to the absorption effect when it propagates in the medium;

[0052] Calculate the grain boundary discontinuity index, construct and solve the joint optimization model of the anisotropic diffusion equation and grain boundary constraint, and obtain the filtered signal. The model expression is: ,in, is the original depth signal, , is an auxiliary variable, , , is the weight parameter, , For depth The depth signal at is the grain boundary discontinuity index, is the target signal to be optimized, represents the interference signal after filtering, for The spatial phase gradient field;

[0053] Through anisotropic dielectric tensor modeling and grain boundary constraint weighting, high-precision separation of the columnar structure of the oxide layer is achieved. Incorporating material physical properties into the filtering algorithm, combined with the efficient Split-Bregman solver, significantly improves the balance between noise suppression and edge preservation, providing a reliable microstructural data foundation for failure analysis of aircraft engine hot end components.

[0054] The present invention is further configured such that the grain boundary discontinuity index is calculated by a normalized ratio of a dielectric constant mutation to a grain size, and its expression is: ,in, is the grain boundary discontinuity index, and is the dielectric constant on both sides of the grain boundary, is the depth position, is the average grain diameter, is the system axial resolution, Represents the dielectric constant component The second moment of is defined as: ,in, is the total number of sampling points in the depth direction of the oxide layer, The formula achieves highly robust quantification of grain boundary discontinuities through dielectric discontinuity strength, global normalization, and size resolution correction, providing a key criterion for the precise separation of columnar crystal structures in aerospace engine oxide layers. By integrating material physical properties with detection system parameters, it significantly improves microscopic feature retention and algorithm adaptability, supporting the construction of a highly reliable life prediction model.

[0055] The present invention is further configured such that the performing time-frequency joint analysis on the filtered signal comprises:

[0056] Adaptive window width adjustment factor is used to optimize the time-frequency transform kernel parameters;

[0057] The optimal time-frequency distribution is generated by maximizing the weighted fitness function of the frequency band energy and signal-to-noise ratio through a genetic algorithm;

[0058] The frequency band energy is nonlinearly compressed based on the hyperbolic tangent function, and the weighted summation of the coefficients calibrated by the oxidation kinetics Arrhenius equation is combined. The Sigmoid function is used to map the coefficients to the physical thickness range to extract the oxide layer thickness and frequency band energy distribution. Specifically, the genetic algorithm optimizes the time-frequency transform kernel, including the following steps:

[0059] Through chromosome encoding, the window parameters Encoded as a binary gene string, defining the search range , , is the cutoff frequency;

[0060] Design a fitness function and output the optimal window parameters when the convergence condition is reached ;

[0061] Use the hyperbolic tangent function to compress the nonlinear effect of frequency band energy: , is the energy of the compressed frequency band, Control compression rate, calibrated by Arrhenius equation;

[0062] According to the compressed frequency band energy, weighted summation and saturation mapping are performed to calculate the oxide layer thickness. The formula is:

[0063] ,in, is the oxide layer thickness, is the oxidation kinetic parameter, is the Sigmoid function, is the reference thickness, To control the saturation rate, is the total number of frequency bands;

[0064] Through adaptive time-frequency analysis, oxidation kinetics calibration, and nonlinear mapping, we achieve high-precision extraction of thermally grown oxide thickness and energy distribution in aircraft engines. By deeply integrating materials science models with signal processing technology, we address the challenges of weak signal detection and physical parameter inversion in high-temperature, high-noise environments, providing a reliable data foundation for engine health management.

[0065] The present invention is further configured such that the adaptive window width adjustment factor is calculated by the elastic coefficient of the frequency band energy to the window scale parameter and the frequency shift cutoff matching degree, and its expression is: ,in, is the adaptive window width adjustment factor, is the total number of frequency bands, For the Band energy, is the window scale parameter, Calculate the frequency band energy elasticity coefficient, about Derivative, representing the window scale parameter Band energy sensitivity, Calculate the frequency shift cutoff matching degree, For the Band shift parameters, is the cutoff frequency, By jointly optimizing the elastic coefficient and frequency shift matching, adaptive adjustment of the time-frequency analysis window width is achieved, solving the resolution imbalance problem of traditional fixed window width in aircraft engine oxide layer detection. Incorporating local signal characteristics into window parameter decision-making significantly improves the physical interpretability and engineering practicality of the time-frequency distribution, providing a high-precision tool for analyzing the dynamic evolution of oxide layers.

[0066] The present invention is further configured such that the cross-scale thermodynamic inversion model construction includes:

[0067] Combining the columnar crystal structure characteristics with the band energy distribution, a multi-field coupled constitutive equation is established, in which the oxidation activation energy is corrected by the grain boundary discontinuity index, and the stress index is modulated nonlinearly by the band energy.

[0068] The parameters of the oxide growth rate equation are solved based on the Bayesian Markov Chain Monte Carlo inversion method, and the uncertainty of the remaining lifetime prediction is quantified in combination with Monte Carlo simulation.

[0069] The inversion parameters are dynamically fed back to the preprocessing step to form a detection-modeling-prediction closed-loop optimization. Specifically, by integrating microstructural characteristics and macroscopic energy distribution, a multi-field coupled oxidation kinetic equation is constructed, and the Bayesian MCMC and Monte Carlo methods are used to achieve high-precision parameter inversion and uncertainty quantification. The grain boundary discontinuity index and frequency band energy are used to correct the activation energy and stress index respectively, breaking through the limitations of traditional single-scale models. The inversion parameters are dynamically fed back to the preprocessing step to form a global optimization of detection-modeling-prediction.

[0070] The present invention is further configured such that the cross-scale thermodynamic inversion model corrects the oxidation activation energy by using a grain boundary discontinuity index, which is expressed as follows: ,in, is the maximum grain boundary discontinuity index, is the dynamic polarization matching factor, is the corrected value of oxidation activation energy, is the baseline oxidation activation energy, is the Boltzmann constant, is the absolute temperature, To adjust the coefficient, specifically, through the joint correction of the grain boundary discontinuity index and the dynamic polarization factor, a cross-scale thermodynamic model of oxidation activation energy is constructed to solve the prediction deviation problem of traditional single-scale models in high temperature and multi-field coupling environments. This model significantly improves the accuracy and reliability of the prediction of the oxide layer life of the hot end components of aircraft engines.

[0071] The present invention is further configured such that the remaining life prediction result is output by jointly solving the oxide layer growth rate equation and the Paris fatigue model, and the expression thereof is: ,in, is the remaining lifetime of the oxide layer, is the current oxide layer thickness, is the critical failure thickness, is the effective stress, is the pre-exponential factor, which represents the frequency factor of the oxidation reaction. is the ideal gas constant, is the stress index, is the oxygen partial pressure contribution coefficient, is the partial pressure of oxygen, is the oxygen partial pressure index, The expression for the oxide layer growth rate is specifically formulated by jointly solving the oxide layer growth rate equation and the Paris fatigue model to construct a high-precision prediction model for the remaining life of thermally grown oxides in aircraft engines. This model integrates the synergistic effects of temperature, stress, and oxygen partial pressure on the oxidation rate, breaks through the limitations of traditional single-field models, and significantly reduces the uncertainty of oxide layer life prediction, providing a key technical guarantee for reducing maintenance costs and avoiding unexpected failures.

[0072] The specific manner in which each module and unit performs operations in the optical coherence tomography detection method for thermally grown oxides in aircraft engines provided in the above-described embodiments has been described in detail in the method embodiments and will not be repeated here. In practical applications, the low-altitude ground-based information fusion system provided in the above-described embodiments can, as needed, distribute the aforementioned functions among different functional modules, i.e., divide the system's internal structure into different functional modules to perform all or part of the aforementioned functions, without limitation herein.

[0073] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via a wired (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0074] It should be understood that the term "and / or" as used herein simply describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A alone, A and B together, or B alone. A and B can be singular or plural. Furthermore, the character " / " as used herein generally indicates an "or" relationship between the associated objects, but it may also indicate an "and / or" relationship. For specific understanding, please refer to the context.

[0075] In this application, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or plural.

[0076] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0077] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0078] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0079] In the several embodiments provided in this application, it should be understood that the disclosed system can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0080] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0081] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0082] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0083] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. An optical coherence tomography method for detecting thermally grown oxides in aircraft engines, characterized in that: include: S1: Collect the interference signal between the reference light field and the sample scattered light field, perform adaptive polarization state compensation on the interference signal based on the dynamic polarization matching factor, and obtain the compensated interference signal; S2: Anisotropic filtering is performed on the compensated interference signal. The signal discontinuity at the columnar crystal boundary is constrained by the grain boundary discontinuity index to retain the signal, the columnar crystal structure characteristics of the oxide layer are separated, and the filtered signal is obtained. A depth-resolved diffusion model is constructed based on the anisotropic dielectric tensor of the columnar crystal structure of the oxide layer. The grain boundary discontinuity index is used to quantify the sudden change in the dielectric constant and weightedly constrain the signal discontinuity retention during the filtering process. An iterative algorithm is used to solve the joint optimization problem of the anisotropic diffusion equation and the grain boundary constraint, the columnar crystal structure characteristics of the oxide layer are separated, and the filtered signal is obtained. The grain boundary discontinuity index is calculated by the normalized ratio of the dielectric constant sudden change to the grain size, and its expression is: ,in, is the grain boundary discontinuity index, and is the dielectric constant on both sides of the grain boundary, is the depth position, is the average grain diameter, is the system axial resolution, Represents the dielectric constant component The second moment of is defined as: ,in, is the total number of sampling points in the depth direction of the oxide layer, is the depth position; S3: Perform time-frequency joint analysis on the filtered signal, optimize the time-frequency transform kernel parameters using the adaptive window width adjustment factor, and extract the oxide layer thickness and frequency band energy distribution; S4: Integrate the columnar crystal structure characteristics and the frequency band energy distribution to construct a cross-scale thermodynamic inversion model and output the prediction results of the remaining life of the engine thermal growth oxide oxide layer. The construction of the cross-scale thermodynamic inversion model includes: integrating the columnar crystal structure characteristics and the frequency band energy distribution to establish a multi-field coupled constitutive equation, in which the oxidation activation energy is corrected by the grain boundary discontinuity index and the stress index is nonlinearly modulated by the frequency band energy; solving the parameters of the oxide layer growth rate equation based on the Bayesian Markov chain Monte Carlo inversion method, and combining Monte Carlo simulation to quantify the uncertainty of the remaining life prediction; the inversion parameters are dynamically fed back to the preprocessing step to form a detection-modeling-prediction closed-loop optimization; the cross-scale thermodynamic inversion model corrects the oxidation activation energy by the grain boundary discontinuity index, and its expression is: ,in, is the maximum grain boundary discontinuity index, is the dynamic polarization matching factor, is the corrected value of oxidation activation energy, is the baseline oxidation activation energy, is the Boltzmann constant, is the absolute temperature, is the adjustment coefficient; the remaining life prediction result is output by jointly solving the oxide layer growth rate equation and the Paris fatigue model, and its expression is: ,in, is the remaining lifetime of the oxide layer, is the current oxide layer thickness, is the critical failure thickness, is the effective stress, is the pre-exponential factor, which represents the frequency factor of the oxidation reaction. is the ideal gas constant, is the stress index, is the oxygen partial pressure contribution coefficient, is the partial pressure of oxygen, is the oxygen partial pressure index, is the expression for the oxide layer growth rate.

2. The optical coherence tomography detection method for thermally grown oxides in aircraft engines according to claim 1, characterized in that: The interference signal between the reference light field and the scattered light field of the sample is collected and analyzed. The phase information of the analyzed signal is extracted, the dynamic polarization matching factor is calculated, a sparse regularized optimization problem is constructed, the polarization compensation matrix is dynamically adjusted, and the polarization state of the interference signal is corrected using the updated polarization compensation matrix to obtain the compensated interference signal.

3. The optical coherence tomography detection method for thermally grown oxides in aircraft engines according to claim 2, characterized in that: The dynamic polarization matching factor is dynamically updated through the sparsity constraint of the phase gradient tensor product and the polarization compensation matrix, and its expression is: ,in, is the dynamic polarization matching factor, is the spatial phase gradient, is the phase distortion field, is the Frobenius norm, is the Jones matrix traces, is the Jones matrix The conjugate transposed matrix of is the adjustment parameter.

4. The optical coherence tomography detection method for thermally grown oxides in aircraft engines according to claim 1, characterized in that: Perform time-frequency joint analysis on the filtered signal, including: Adaptive window width adjustment factor is used to optimize the time-frequency transform kernel parameters; The optimal time-frequency distribution is generated by maximizing the weighted fitness function of the frequency band energy and signal-to-noise ratio through a genetic algorithm; The band energy is nonlinearly compressed based on the hyperbolic tangent function, and the weighted summation of the coefficients calibrated by the oxidation kinetics Arrhenius equation is combined. The Sigmoid function is used to map the energy to the physical thickness range to extract the oxide layer thickness and band energy distribution.

5. The optical coherence tomography detection method for thermally grown oxides in aircraft engines according to claim 4, characterized in that: The adaptive window width adjustment factor is calculated by the elastic coefficient of the band energy to the window scale parameter and the frequency shift cutoff matching degree, and its expression is: ,in, is the adaptive window width adjustment factor, is the total number of frequency bands, For the Band energy, is the window scale parameter, Calculate the frequency band energy elastic coefficient, Calculate the frequency shift cutoff matching degree, For the Band shift parameters, is the cutoff frequency, .

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